Serous surface papillary borderline ovarian tumors: correlation of sonographic features with clinic pathological findings

Serous surface papillary borderline ovarian tumor (SSPBOT) is a distinct subtype of serous borderline ovarian tumor characterized by solid tissue deposition confined to the ovarian surface. Because SSPBOT is rare, there are few published reports on the ultrasonographic features of this condition. In this retrospective study, we investigated 12 cases of SSPBOT. Ultrasound imaging of SSPBOT showed grossly normal ovaries that were encased partially or wholly by tumor deposits that were confined to the surface, with clear demarcation between normal ovarian tissue and surrounding tumors. Color Doppler imaging demonstrated the 'fireworks sign' in all cases of SSPBOT, corresponding to an intratumoral vascular bundle originating from the ovarian vessels and supplying hierarchical branching blood flow to the surrounding tumor. No patient with ovarian high-grade serous carcinoma showed these morphological and Doppler features. In our series, the fireworks sign appeared to be a characteristic feature of SSPBOT that could facilitate correct identification of this tumor. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Predicting Two-Photon Absorption Spectra of Octupolar Molecules: A Deep-Learning Approach Based Exclusively on Molecular Structures

Octupolar molecules possessing a strong two-photon response are vital for numerous advanced applications. However, accurately predicting their two-photon absorption (TPA) spectra requires high-precision quantum chemical calculations, which are computationally expensive due to repeated simulations of molecular excited-state properties. To address this challenge, we introduce a deep learning approach capable of rapidly and accurately forecasting TPA spectra for octupolar molecules. By leveraging the geometric structure as an initial descriptor, we employ a graph neural network to predict the maximum two-photon transition wavelength and cross-section. Our model demonstrates a mean absolute percentage error of less than 4% compared to time-dependent density-functional theory calculations, effectively reproducing experimental observations. Notably, this deep learning technique is nearly 100 000 times faster than comparable quantum calculations, making it an efficient and cost-effective tool for simulating TPA properties of octupolar molecules. Furthermore, this method holds great promise for the high-throughput screening of exceptional TPA materials.

Multilevel Laser-Induced Pain Measurement with Wasserstein Generative Adversarial Network - Gradient Penalty Model

Pain is an experience of unpleasant sensations and emotions associated with actual or potential tissue damage. In the global context, billions of people are affected by pain disorders. There are particular challenges in the measurement and assessment of pain, and the commonly used pain measuring tools include traditional subjective scoring methods and biomarker-based measures. The main tools for biomarker-based analysis are electroencephalography (EEG), electrocardiography and functional magnetic resonance. The EEG-based quantitative pain measurements are of immense value in clinical pain management and can provide objective assessments of pain intensity. The assessment of pain is now primarily limited to the identification of the presence or absence of pain, with less research on multilevel pain. High power laser stimulation pain experimental paradigm and five pain level classification methods based on EEG data augmentation are presented. First, the EEG features are extracted using modified S-transform, and the time-frequency information of the features is retained. Based on the pain recognition effect, the 20-40[Formula: see text]Hz frequency band features are optimized. Afterwards the Wasserstein generative adversarial network with gradient penalty is used for feature data augmentation. It can be inferred from the good classification performance of features in the parietal region of the brain that the sensory function of the parietal lobe region is effectively activated during the occurrence of pain. By comparing the latest data augmentation methods and classification algorithms, the proposed method has significant advantages for the five-level pain dataset. This research provides new ways of thinking and research methods related to pain recognition, which is essential for the study of neural mechanisms and regulatory mechanisms of pain.

Self-Supervised EEG Representation Learning with Contrastive Predictive Coding for Post-Stroke Patients

Stroke patients are prone to fatigue during the EEG acquisition procedure, and experiments have high requirements on cognition and physical limitations of subjects. Therefore, how to learn effective feature representation is very important. Deep learning networks have been widely used in motor imagery (MI) based brain-computer interface (BCI). This paper proposes a contrast predictive coding (CPC) framework based on the modified s-transform (MST) to generate MST-CPC feature representations. MST is used to acquire the temporal-frequency feature to improve the decoding performance for MI task recognition. EEG2Image is used to convert multi-channel one-dimensional EEG into two-dimensional EEG topography. High-level feature representations are generated by CPC which consists of an encoder and autoregressive model. Finally, the effectiveness of generated features is verified by the k-means clustering algorithm. It can be found that our model generates features with high efficiency and a good clustering effect. After classification performance evaluation, the average classification accuracy of MI tasks is 89% based on 40 subjects. The proposed method can obtain effective feature representations and improve the performance of MI-BCI systems. By comparing several self-supervised methods on the public dataset, it can be concluded that the MST-CPC model has the highest average accuracy. This is a breakthrough in the combination of self-supervised learning and image processing of EEG signals. It is helpful to provide effective rehabilitation training for stroke patients to promote motor function recovery.

A Light Vehicle License-Plate-Recognition System Based on Hybrid Edge-Cloud Computing

With the world moving towards low-carbon and environmentally friendly development, the rapid growth of new-energy vehicles is evident. The utilization of deep-learning-based license-plate-recognition (LPR) algorithms has become widespread. However, existing LPR systems have difficulty achieving timely, effective, and energy-saving recognition due to their inherent limitations such as high latency and energy consumption. An innovative Edge-LPR system that leverages edge computing and lightweight network models is proposed in this paper. With the help of this technology, the excessive reliance on the computational capacity and the uneven implementation of resources of cloud computing can be successfully mitigated. The system is specifically a simple LPR. Channel pruning was used to reconstruct the backbone layer, reduce the network model parameters, and effectively reduce the GPU resource consumption. By utilizing the computing resources of the Intel second-generation computing stick, the network models were deployed on edge gateways to detect license plates directly. The reliability and effectiveness of the Edge-LPR system were validated through the experimental analysis of the CCPD standard dataset and real-time monitoring dataset from charging stations. The experimental results from the CCPD common dataset demonstrated that the network's total number of parameters was only 0.606 MB, with an impressive accuracy rate of 97%.

A deep learning model for predicting selected organic molecular spectra

Accurate and efficient molecular spectra simulations are crucial for substance discovery and structure identification. However, the conventional approach of relying on the quantum chemistry is cost intensive, which hampers efficiency. Here we develop DetaNet, a deep-learning model combining E(3)-equivariance group and self-attention mechanism to predict molecular spectra with improved efficiency and accuracy. By passing high-order geometric tensorial messages, DetaNet is able to generate a wide variety of molecular properties, including scalars, vectors, and second- and third-order tensors-all at the accuracy of quantum chemistry calculations. Based on this we developed generalized modules to predict four important types of molecular spectra, namely infrared, Raman, ultraviolet-visible, and 1H and 13C nuclear magnetic resonance, taking the QM9S dataset containing 130,000 molecular species as an example. By speeding up the prediction of molecular spectra at quantum chemical accuracy, DetaNet could help progress toward real-time structural identification using spectroscopic measurements.

Theoretical Insights on the Sensing Performance for Newly-synthesized Two-photon Fluorescent N2H4 Probes Based on Spirobifluorence

The development of fluorescent probe for hydrazine (N2H4) detection has attracted much attention due to the important role of N2H4 plays in the fields of medicine, agriculture, biology and environments. In this paper, the optical properties and water solubility of two novel two-photon fluorescent molecular probes (Probe1 and Probe2) before and after the reaction with N2H4 are studied by using the density function theory. The results show that electronic distribution and transition dipole moment of the probes are obviously changed after the reaction with N2H4, thus the optical properties of the molecules are influenced and the detection of N2H4 are realized. In addition, photoinduced electron transfer processes for Probe1 and Probe2 in the presence of N2H4 are theoretically characterized, which explains the experimental observations from the microscopic mechanism. Special attention has been paid on the analysis of the two-photon absorption for the probes with the absence and presence of N2H4 by the response theory method. Both probes with good water solubility show large variation on the two-photon absorption cross section when reacts with N2H4. In particular, the two-photon absorption response of Probe2 is more obvious, so it possesses preferable two-photon fluorescence microscopic imaging ability. More importantly, the receptor effect on the sensing performances of the probes are demonstrated, providing a theoretical reference for the design and synthesis on more efficient two-photon fluorescence N2H4 probes. Our study provides necessary information on the response mechanism of the studied chemosensors and helps to establish the relationship between the structure and optical properties of two-photon fluorescence N2H4 probes.

Revealing the influence of doping elements (Ge, Sn, Ca, and Sr) on the properties of α-CsPbI3: a DFT investigation

In this study, using density functional theory, we calculated the band structure and photoelectric properties in a series of 12.5% B-doped (B = Ge, Sn, Ca, and Sr) CsPbI3 perovskite systems. It is found that Ge doping can improve the structural stability and is more conducive to applications under high-pressure or by applying stress via calculating the bond length, formation energy, elastic properties, and electronic local function. In addition, the optimal direction for applying stress is achieved according to the elastic properties. Furthermore, in terms of electronic properties, the reason of energy band variation and the influence of chemical bond on the structural stability of doped α-CsPbI3 are investigated. The possibility of the applications of the CsPb0.875B0.125I3 perovskite is explored based on the optical properties. Thus, the theoretical study of the CsPb0.875B0.125I3 perovskite provides novel insights into the design of next-generation photoelectric and photovoltaic materials.

One-Dimensional Local Binary Pattern and Common Spatial Pattern Feature Fusion Brain Network for Central Neuropathic Pain

Central neuropathic pain (CNP) after spinal cord injury (SCI) is related to the plasticity of cerebral cortex. The plasticity of cortex recorded by electroencephalogram (EEG) signal can be used as a biomarker of CNP. To analyze changes in the brain network mechanism under the combined effect of injury and pain or under the effect of pain, this paper mainly studies the changes of brain network functional connectivity in patients with neuropathic pain and without neuropathic pain after SCI. This paper has recorded the EEG with the CNP group after SCI, without the CNP group after SCI, and a healthy control group. Phase-locking value has been used to construct brain network topological connectivity maps. By comparing the brain networks of the two groups of SCI with the healthy group, it has been found that in the [Formula: see text] and [Formula: see text] frequency bands, the injury increases the functional connectivity between the frontal lobe and occipital lobes, temporal, and parietal of the patients. Furthermore, the comparison of brain networks between the group with CNP and the group without CNP after SCI has found that pain has a greater effect on the increased connectivity within the patients' frontal lobes. Motor imagery (MI) data of CNP patients have been used to extract one-dimensional local binary pattern (1D-LBP) and common spatial pattern (CSP) features, the left and right hand movements of the patients' MI have been classified. The proposed LBP-CSP feature method has achieved the highest accuracy of 98.6% and the average accuracy of 91.5%. The results of this study have great clinical significance for the neural rehabilitation and brain-computer interface of CNP patients.

Influence of Sr doping on the photoelectronic properties of CsPbX3 (X = Cl, Br, or I): a DFT investigation

To broaden the application of cesium lead halide perovskites, doping technology has been widely proposed. In this study, we calculated a 12.5% concentration of a Sr-doped CsPbX₃ (X = Cl, Br, or I) perovskite via density functional theory. The results showed that the bandgap energy of the perovskite increased by 0.2-0.3 eV. The high symmetry points of the energy band changed from R to Γ after Sr doping because the Sr doping affected the initial distribution of atomic orbital hybridization. In addition, optical absorption spectra after doping showed an obvious blueshift, whereas the absorption coefficient of CsPb_0.875Sr_0.125X₃ had the same magnitude as undoped CsPbX₃. Moreover, the effective masses of electrons and holes changed within a small range (0.01-0.03 m₀) after Sr doping. According to the findings of this study, the CsPb_0.875Sr_0.125X₃ perovskite is expected to become an ideal candidate material for designing photovoltaic and photoelectric devices.

Exploration of sleep function connection and classification strategies based on sub-period sleep stages

Background

As a medium for developing brain-computer interface systems, EEG signals are complex and difficult to identify due to their complexity, weakness, and differences between subjects. At present, most of the current research on sleep EEG signals are single-channel and dual-channel, ignoring the research on the relationship between different brain regions. Brain functional connectivity is considered to be closely related to brain activity and can be used to study the interaction relationship between brain areas.

Methods

Phase-locked value (PLV) is used to construct a functional connection network. The connection network is used to analyze the connection mechanism and brain interaction in different sleep stages. Firstly, the entire EEG signal is divided into multiple sub-periods. Secondly, Phase-locked value is used for feature extraction on the sub-periods. Thirdly, the PLV of multiple sub-periods is used for feature fusion. Fourthly, the classification performance optimization strategy is used to discuss the impact of different frequency bands on sleep stage classification performance and to find the optimal frequency band. Finally, the brain function network is constructed by using the average value of the fusion features to analyze the interaction of brain regions in different frequency bands during sleep stages.

Results

The experimental results have shown that when the number of sub-periods is 30, the α (8-13 Hz) frequency band has the best classification effect, The classification result after 10-fold cross-validation reaches 92.59%.

Conclusion

The proposed algorithm has good sleep staging performance, which can effectively promote the development and application of an EEG sleep staging system.

Coherence based graph convolution network for motor imagery-induced EEG after spinal cord injury

Background

Spinal cord injury (SCI) may lead to impaired motor function, autonomic nervous system dysfunction, and other dysfunctions. Brain-computer Interface (BCI) system based on motor imagery (MI) can provide more scientific and effective treatment solutions for SCI patients.

Methods

According to the interaction between brain regions, a coherence-based graph convolutional network (C-GCN) method is proposed to extract the temporal-frequency-spatial features and functional connectivity information of EEG signals. The proposed algorithm constructs multi-channel EEG features based on coherence networks as graphical signals and then classifies MI tasks. Different from the traditional graphical convolutional neural network (GCN), the C-GCN method uses the coherence network of EEG signals to determine MI-related functional connections, which are used to represent the intrinsic connections between EEG channels in different rhythms and different MI tasks. EEG data of SCI patients and healthy subjects have been analyzed, where healthy subjects served as the control group.

Results

The experimental results show that the C-GCN method can achieve the best classification performance with certain reliability and stability, the highest classification accuracy is 96.85%.

Conclusion

The proposed framework can provide an effective theoretical basis for the rehabilitation treatment of SCI patients.

Theoretical study on a series of naphthalimide-contained two-photon fluorescent hypochlorite probe targeting endoplasmic reticulum: response mechanism and receptor effect

The development of detecting hypochlorous acid (HClO) in living endoplasmic reticulum has attracted much attention in the fields of biology, medicine, and pharmacy. In the present work, the one-photon absorption (OPA), one-photon emission (OPE), and two-photon absorption (TPA) properties of a series newly synthesized chemosensors with naphthalimide as the fluorophore were systematically investigated using time-dependent density functional theory in combination with response theory. Special emphasis is placed on evolution of the probes' optical properties in the presence of HClO. These compounds show drastic changes in their photoabsorption and photoemission properties when they react with HClO, indicating them to be excellent candidates as fluorescent chemosensors. To further understand the mechanisms of the two probes, we have employed the hole and electron analysis to investigate the charge transfer process for the photoemission of the molecules. The receptor effect is found to play a dominant role in the sensing performance of these probes. Specifically, two-photon absorption properties of the molecules are calculated. We have found that all probes show significant two-photon responses in the near-infrared light region. And the maximum two-photon absorption cross section of probe 2 is greatly enhanced with the presence of HClO, indicating that probe 2 can act as a potential two-photon excited fluorescent HClO probe. The theoretical investigations would be helpful to build the structure-property relationships for the naphthalimide-contained probes, providing information on the design of efficient two-photon fluorescent sensors that can be used for biological imaging of HClO in endoplasmic reticulum.

Electronic Structures and Photoelectric Properties in Cs3Sb2X9 (X = Cl, Br, or I) under High Pressure: A First Principles Study

Lead-free perovskites of Cs₃Sb₂X₉ (X = Cl, Br, or I) have attracted wide attention owing to their low toxicity. High pressure is an effective and reversible method to tune bandgap without changing the chemical composition. Here, the structural and photoelectric properties of Cs₃Sb₂X₉ under high pressure were theoretically studied by using the density functional theory. The results showed that the ideal bandgap for Cs₃Sb₂X₉ can be achieved by applying high pressure. Moreover, it was found that the change of the bandgap is caused by the shrinkage of the Sb-X long bond in the [Sb₂X₉]^3- polyhedra. Partial density of states indicated that Sb-5s and X-p orbitals contribute to the top of the valence band, while Sb-5p and X-p orbitals dominate the bottom of the conduction band. Moreover, the band structure and density of states showed significant metallicity at 38.75, 24.05 GPa for Cs₃Sb₂Br₉ and Cs₃Sb₂I₉, respectively. Moreover, the absorption spectra showed the absorption edge redshifted, and the absorption coefficient of the Cs₃Sb₂X₉ increased under high pressure. According to our calculated results, the narrow bandgap and enhanced absorption ability under high pressure provide a new idea for the design of the photovoltaic and photoelectric devices.

Versatile Dicyanomethylene-Based Fluorescent Probes for the Detection of β-Amyloid in Alzheimer’s Disease: A Theoretical Perspective

Motivated by the growing demand for target chemosensors designed with diagnostic or therapeutic capability for fibrils related to amyloidosis diseases, we investigated in the present work the response mechanism of dicyanomethylene-based fluorescent probes for amyloid fibril using a combined approach, including molecular docking, quantum mechanics/molecular mechanics (QM/MM), and the quantum chemical method. Various binding modes for the probes in β-amyloid (Aβ) are discussed, and the fibril environment-induced molecular optical changes at the most stable site are compared to the fibril-free situation in aqueous environments. The results reveal that the fluorescence enhancement for the probes in Aβ observed experimentally is an average consequence over multiple binding sites. In particular, the conformational difference, including conjugation length and donor effect, significantly contributes to the optical property of the studied probes both in water and fibril. To further estimate the transition nature of the molecular photoabsorption and photoemission processes, the hole-electron distribution and the structural variation on the first excited state of the probes are investigated in detail. On the basis of the calculations, structure–property relationships for the studied chemosensors are established. Our computational approach with the ability to elucidate the available experimental results can be used for designing novel molecular probes with applications to Aβ imaging and the early diagnosis of Alzheimer’s disease.

Ultrafast and Polarization-Sensitive ReS2/ReSe2 Heterostructure Photodetectors with Ambipolar Photoresponse

Recently, two-dimensional (2D) van der Waals (vdWs) heterostructures provided excellent and fascinating platforms for advanced engineering in high-performance optoelectronic devices. Herein, novel ReS2/ReSe2 heterojunction phototransistors are constructed and explored systematically that display high responsivity, wavelength-dependent ambipolar photoresponse (negative and positive), ultrafast and polarization-sensitive detection capability. This photodetector exhibits a positive photoresponse from UV to visible spectrum (760 nm) with high photoresponsivities about 126.56 and 16.24 A/W under 350 and 638 nm light illumination, respectively, with a negative photoresponse over 760 nm, which is mainly ascribed to the ambipolar photoresponse modulated by gate voltage. In addition, profound linear polarization sensitivity is demonstrated with a dichroic ratio of about ∼1.2 at 638 nm and up to ∼2.0 at 980 nm, primarily owing to the wavelength-dependent absorption anisotropy and the stagger alignment of the crystal. Beyond static photodetection, the dynamic photoresponse of this vdWs device presents an ultrafast and repeatable photoswitching performance with a cutoff frequency (f3dB) exceeding 100 kHz. Overall, this study reveals the great potential of 2D ReX2-based vdWs heterostructures for high-performance, ultrafast, and polarization-sensitive broadband photodetectors.

Direct generation of continuous-wave and passively Q-switched visible vortex beams from a doughnut-shaped diode-pumped Pr: YLF laser

We demonstrate the direct generation of visible vortex beams (LG₀₁ mode) from a doughnut-shaped diode-pumped Pr:YLF laser. In continuous-wave mode, the maximum vortex output power was 36 mW at 523 nm, 354 mW at 607 nm, 838 mW at 639 nm, 722 mW at 721 nm, respectively. Moreover, based on this operation, the orange and red passively Q-switched vortex lasers were also achieved by inserting a Co:MgAl₂O₄ crystal into the laser cavity as a saturable absorber. The shortest pulse width of Q-switched vortex laser was 58 ns for 607 nm, and 34 ns for 639 nm, respectively. Our work provides a reliable and efficient method for the direct generation of visible vortex lasers for potential applications.

Theoretical Investigation of Switch Effect on the Efficiency and Adaptivity of Molecular Optoelectronic Conversion Devices

Molecular photoswitch can effectively regulate charge separation (CS) and charge recombination (CR) in donor-acceptor (D-A) systems. However, deformation of the donor-switch-acceptor (D-S-A) systems caused by the switch isomerization will destroy the geometrical stability of the battery. Here we take the planar platinum(II) terpyridyl complex of [Pt(^t Bu₃ tpy)(-C≡C-Ph)_n ]⁺ as the typical D-A model, designed six D-S-A systems using different photoswitches (dimethyldihydropyrene, fulgimide, arylazopyrazole, N-salicylideneaniline, spiropyran, and dithienylethene, denoted as D-S-A 1-6 hereafter). Our investigations show that the D-S-A 1-6 can absorb visible light of 799 nm, 673 nm, 527 nm, 568 nm, 616 nm, and 629 nm, facilitating electrons transfer from the donor and the switch to the acceptor through the Switch-on channel. Then cationic character of the photoswitch can undergo much more rapid isomerization than the neutral form due to the lower energy barrier. The Switch-off isomer breaks the conjugation of the D-S-A system, effectively turning off the CT channel and forming the CS state. Based on the evaluated conjugated backbone twist (CBT) angle, we found that D-S-A 1, 2, 4, 6 exhibit little configurational change and can be good candidates as the organic solar cell. The proposed D-S-A design controlled by the molecular switch may help to develop a solution for solar-harvesting practical applications.

Time-Varying Effective Connectivity for Describing the Dynamic Brain Networks of Post-stroke Rehabilitation

Hemiplegia is a common motor dysfunction caused by a stroke. However, the dynamic network mechanism of brain processing information in post-stroke hemiplegic patients has not been revealed when performing motor imagery (MI) tasks. We acquire electroencephalography (EEG) data from healthy subjects and post-stroke hemiplegic patients and use the Fugl-Meyer assessment (FMA) to assess the degree of motor function damage in stroke patients. Time-varying MI networks are constructed using the adaptive directed transfer function (ADTF) method to explore the dynamic network mechanism of MI in post-stroke hemiplegic patients. Finally, correlation analysis has been conducted to study potential relationships between global efficiency and FMA scores. The performance of our proposed method has shown that the brain network pattern of stroke patients does not significantly change from laterality to bilateral symmetry when performing MI recognition. The main change is that the contralateral motor areas of the brain damage and the effective connection between the frontal lobe and the non-motor areas are enhanced, to compensate for motor dysfunction in stroke patients. We also find that there is a correlation between FMA scores and global efficiency. These findings help us better understand the dynamic brain network of patients with post-stroke when processing MI information. The network properties may provide a reliable biomarker for the objective evaluation of the functional rehabilitation diagnosis of stroke patients.

Abnormal actions detection of robotic arm via 3D convolution neural network and support vector data description

Robotic arms are powerful assistants in many industrial production environments, and they run periodically in accordance with preset actions to complete specified operations. However, they may act abnormally when encountering unexpected situation and then lead to unnecessary loss. Recognizing the abnormal actions of robotic arms through surveillance video can automatically help us to understand their operating status and discover possible abnormalities in time. We designed a deep learning architecture based on 3D convolution for abnormal action recognition. The 3D convolutional layer can extract the spatial and temporal features of the robotic arm movements from the video frame difference sequence. The features are compressed and streamlined by the maximum pooling layer to obtain concise and effective robotic arm action features. Finally, the fully connected layer is used to classify the features to recognize the abnormal robotic arm tasks. Support vector data description (SVDD) model is employed to detect abnormal actions of the robotic arm, and the well-trained SVDD model can distinguish the normal actions from the three kinds of abnormal actions with the Area Under Curve (AUC) 99.17%.

Triplet exciton dynamics of pure organics with halogen substitution boosted two photon absorption and room temperature phosphorescence: A theoretical perspective

Organic room temperature phosphorescence (RTP) molecules have shown promising applications in organic light emitting diodes and vivo imaging. Thus, triplet exciton dynamics in solid phase should be revealed and the molecule should possess large two photon absorption (TPA) cross sections under near-infrared excitation. The effects of halogen substitution and intermolecular interaction on RTP and TPA properties are studied at molecular level for a series of derivatives. Surrounding environment in solid phase is considered by combined quantum mechanics and molecular mechanics method. Intermolecular interactions are evaluated by the independent gradient model and calculated through the molecular force field energy decomposition method. Minimum energy crossing point, Huang-Rhys factor and reorganization energy are discussed, triplet exciton dynamics are investigated by thermal vibration correlation function method. Results indicate that the largest TPA cross sections are found for molecule in water. The halogen substitution can enlarge the proportion of (π, π*) and facilitate the intersystem crossing process. Restricted intramolecular rotation motions of dihedral angle in low frequency regions are found for Br-Np-Cz-BF₂ in solid phase. While enhanced vibrations of bond length and bond angle in high frequency regions are detected for I-Np-Cz-BF₂. Effects of halogen substitution and intermolecular interaction on triplet exciton dynamics are highlighted.

Designing Self-Adaptive Donor-Switch-Acceptor for Molecular Opto-Electronic Conversion Based on Dimethyldihydropyrene/Cyclophanediene

Introduction of self-adaptive molecular switch is an appealing strategy to achieve complete charge separation (CS) in donor-acceptor (D-A) systems. Here we designed donor-switch-acceptor (D-S-A) systems using the platinum(II) terpyridyl complex as the acceptor, the dimethyldihydropyrene /cyclophanediene (DHP/CPD) as the bridge, and the methoxybenzene, thieno[3,​2-​ b ]thiophene, 2,2'-bifuran, and 4,8-dimethoxybenzo[1,2-b:4,5-b']difuran as the donors, respectively. We then systematically studied the whole opto-electronic conversion process of the donor-DHP/CPD-acceptor (D-DHP/CPD-A) systems based on time-dependent density functional theory, time-dependent ultrafast electron evolution, and electron transport property calculations. We first found that the substitution of -CH 3 by -H and -CN groups in DHP/CPD can enlarge the range of the adsorption wavenumber in opto-electric conversion. Then the light absorption induces the cationization of DHP switch, largely accelerating the forth-isomerization to CPD form. Once the D-CPD-A molecule is formed, the poor conjugation can realize the complete CS state by inhibiting the radiative and nonradiative charge recombinations. Finally, the repeatable and complete CS can be achieved through the automatic back-isomerization of CPD to DHP. The present work provides valuable insights into design of D-S-A systems for practical utilization of molecule-based solar harvesting.

Strain-induced bandgap engineering in CsGeX3 (X = I, Br or Cl) perovskites: insights from first-principles calculations

Based on density functional theory and following first-principles methods, this paper investigated the electronic structures, densities of states, effective masses of electrons and holes, and optical properties of CsGeX₃ (X = I, Br or Cl) perovskites under triaxial strains of -4% to 4%. The calculated results show that the tuning range of the bandgaps of the CsGeI₃, CsGeBr₃, and CsGeCl₃ perovskites are 1.16 eV, 1.64 eV, and 1.63 eV, respectively. This result shows that the bandgap of the CsGeX₃ perovskite is tuned over the entire visible spectrum by applying strain. Also, it is found that the change of the bandgap is caused by the change of the Ge-X long bond. Besides, the optimal bandgaps of CsGeI₃ and CsGeBr₃ can be achieved by applying compressive strains, providing theoretical support for adjusting the bandgaps of CsGeX₃ perovskites. The effective masses of electrons and holes of CsGeX₃ perovskites decrease gradually with the strains changing from 4% to -4%, which is conducive to the transmission of electrons and holes. In addition, the optical properties of CsGeX₃ perovskites change from redshifted to blueshifted under different strains.

Passively mode-locked red Pr:LiYF4 laser based on a two-dimensional palladium diselenide saturable absorber

We report a passively mode-locked Pr:LiYF₄ (Pr:YLF) visible laser using a palladium diselenide (PdSe₂) as a saturable absorber (SA) for the first time, to the best of our knowledge. The nonlinear optical properties of two-dimensional (2D) PdSe₂ nanosheets in the visible band were studied by the open-aperture Z-scan technique. The results indicate the significant saturable absorption properties of PdSe₂ nanosheets in the visible region. Furthermore, the continuous wave mode-locked (CWML) visible laser based on PdSe₂ SA was successfully realized. Ultrashort pulses as short as 35 ps were obtained at 639.5 nm with a repetition rate of 80.3 MHz and a maximum output power of 116 mW. The corresponding pulse energy was 1.44 nJ and peak power was 41.3 W. These results indicate that 2D PdSe₂ SA is a promising high stability passively mode-locked device for ultrafast solid-state visible lasers.

A novel 2-(aminomethyl)pyridineH2PO4 crystal with second-order nonlinear optical performance

Single-crystal structure diagram and SHG response of (2-Ampy)H2PO4 crystal.

Optical Properties of GaN-Based Green Light-Emitting Diodes Influenced by Low-Temperature p-GaN Layer

GaN-based green light-emitting diodes (LEDs) with different thicknesses of the low-temperature (LT) p-GaN layer between the last GaN barriers and p-AlGaN electron blocking layer were characterized by photoluminescence (PL) and electroluminescence (EL) spectroscopic methods in the temperature range of 6–300 K and injection current range of 0.01–350 mA. Based on the results, we suggest that a 20 nm-thick LT p-GaN layer can effectively prevent indium (In) re-evaporation, improve the quantum-confined Stark effect in the last quantum well (QW) of the active region, and finally reduce the efficiency droop by about 7%.

Towards advanced aqueous zinc battery by exploiting synergistic effects between crystalline phosphide and amorphous phosphate

High-performance aqueous zinc batteries are expected to be realized, rooting from component synergistic effects of the hierarchical composite electrode materials. Herein, hierarchical crystalline Ni-Co phosphide coated with amorphous phosphate nanoarrays (C-NiCoP@A-NiCoPO₄) self-supporting on the Ni foam are constructed as cathode material of an aqueous zinc battery. In this unique core-shell structure, the hexagonal phosphide with high conductivity offers ultra-fast electronic transmission and amorphous phosphate with high stability, and open-framework provides more favorable ion diffusivity and a stable protective barrier. The synergistic effects of this intriguing core-shell structure endow the electrode material with outstanding reaction kinetics and structural stability, which is theoretically confirmed by density functional theory (DFT) calculations. As a result, the C-NiCoP@A-NiCoPO₄ electrode exhibits a higher specific capacity of 350.6 mA h g^-1 and excellent cyclic stability with 92.6% retention after 10 000 cycles. Moreover, the C-NiCoP@A-NiCoPO₄ is coupled with Zn anode to assemble an aqueous pouch battery that delivers ultra-high energy density (626.33 W h kg^-1 at 1.72 kW kg^-1) with extraordinary rate performance (452.05 W h kg^-1 at 33.56 kW kg^-1). Moreover, the corresponding quasi-solid flexible battery with polyacrylamide hydrogel electrolyte exhibits favorable durability under frequent mechanical strains, which indicates the great promise of crystalline/amorphous hierarchical electrodes in the field of energy storage.

Classification of left-versus right-hand motor imagery in stroke patients using supplementary data generated by CycleGAN

Acquiring Electroencephalography (EEG) data is often time-consuming, laborious, and costly, posing practical challenges to train powerful but data-demanding deep learning models. This study proposes a surrogate EEG data-generation system based on cycle-consistent adversarial networks (CycleGAN) that can expand the number of training data. This study used EEG2Image based on a modified S-transform (MST) to convert EEG data into EEG-topography. This method retains the frequency-domain characteristics and spatial information of the EEG signals. Then, the CycleGAN is used to learn and generate motor-imagery EEG data of stroke patients. From the visual inspection, there is no difference between the EEG topographies of the generated and original EEG data collected from the stroke patients. Finally, we used convolutional neural networks (CNN) to evaluate and analyze the generated EEG data. The experimental results show that the generated data effectively improved the classification accuracy.

Dimension-Dependent Bandgap Narrowing and Metallization in Lead-Free Halide Perovskite Cs3Bi2X9 (X = I, Br, and Cl) under High Pressure

Low-toxicity, air-stable cesium bismuth iodide Cs3Bi2X9 (X = I, Br, and Cl) perovskites are gaining substantial attention owing to their excellent potential in photoelectric and photovoltaic applications. In this work, the lattice constants, band structures, density of states, and optical properties of the Cs3Bi2X9 under high pressure perovskites are theoretically studied using the density functional theory. The calculated results show that the changes in the bandgap of the zero-dimensional Cs3Bi2I9, one-dimensional Cs3Bi2Cl9, and two-dimensional Cs3Bi2Br9 perovskites are 3.05, 1.95, and 2.39 eV under a pressure change from 0 to 40 GPa, respectively. Furthermore, it was found that the optimal bandgaps of the Shockley-Queisser theory for the Cs3Bi2I9, Cs3Bi2Br9, and Cs3Bi2Cl9 perovskites can be reached at 2-3, 21-26, and 25-29 GPa, respectively. The Cs3Bi2I9 perovskite was found to transform from a semiconductor into a metal at a pressure of 17.3 GPa. The lattice constants, unit-cell volume, and bandgaps of the Cs3Bi2X9 perovskites exhibit a strong dependence on dimension. Additionally, the Cs3Bi2X9 perovskites have large absorption coefficients in the visible region, and their absorption coefficients undergo a redshift with increasing pressure. The theoretical calculation results obtained in this work strengthen the fundamental understanding of the structures and bandgaps of Cs3Bi2X9 perovskites at high pressures, providing a theoretical support for the design of materials under high pressure.

Responsive mechanism of 2-fluoro-5-nitrobenzoate based two-photon fluorescent probes for H2Sn detection: A theoretical perspective

Two-photon fluorescent probes with large two-photon absorption (TPA) cross sections have shown wide applications in biomedical domain. However, both the species and amounts of high efficient probes are far from meeting the requirements, one main reason is that the relationship between the molecular structures and the responsive mechanisms are not clear and theoretical framework in this field is not perfect. In this work, the photophysical properties including one- and two-photon absorption and emission of three newly synthesized fluorescent probes for hydrogen polysulfide (H₂S_n) detection are investigated by density functional theory and time-dependent density functional theory with the polarizable continuum model in different solvents. Results indicate that the enhanced fluorescent intensity and enlarged TPA cross section can be found when the probes reacted with H₂S_n. Moreover, the OPA intensity is largest and its fluorescent intensity is largely enhanced when detecting H₂S_n for Pro2, this verifies its superior performance in the detection of H₂S_n than Pro1 and Pro 3. Furthermore, the inner mechanism for the increase of TPA cross section is revealed, the responsive mechanisms for photo induced electron transfer (PET) and fluorescence resonance energy transfer (FRET) processes are revealed through analyzing the energies and distributions of frontier orbitals. Our calculations provide theoretical perspectives for experimental measurements and could sever as a useful reference for developing advanced probes in biomedical fields.

The contact barrier of a 1T'/2H MoS2 heterophase bilayer and its modulation by adatom and strain: a first-principles study

The successful synthesis of a 1T'/2H MoS₂ heterophase bilayer offers potential building blocks for constructing novel nanoelectronic and optoelectronic devices. Here, first principles calculations are applied to explore and modulate its contact nature. The calculated results show a finite Schottky barrier of ∼0.56 eV, and a dominant tunneling barrier of ∼2 eV exists at the contact interface of the 1T'/2H MoS₂ heterophase bilayer. The Schottky barrier can be eliminated by adatoms and strains. Although the two strategies have an insignificant effect on the dominant tunneling barrier, they alter the regions with local potentials lower than that of the inter-layer gap related barrier.

Theoretical perspective on the luminescence mechanism of a hybridized local and charge transfer state emitter with aggregation induced emission: a QM/MM study

Relationship among basic molecular structures and intermolecular interactions as well as AIE–HLCT mechanisms are theoretically revealed.

Bugs and drugs: a systems biology approach to characterising the effect of moxidectin on the horse's faecal microbiome

Background

Anthelmintic treatment is a risk factor for intestinal disease in the horse, known as colic. However the mechanisms involved in the onset of disease post anthelmintic treatment are unknown. The interaction between anthelmintic drugs and the gut microbiota may be associated with this observed increase in risk of colic. Little is known about the interaction between gut microbiota and anthelmintics and how treatment may alter microbiome function. The objectives of this study were: To characterise (1) faecal microbiota, (2) feed fermentation kinetics in vitro and (3) metabolic profiles following moxidectin administration to horses with very low (0 epg) adult strongyle burdens. Hypothesis: Moxidectin will not alter (1) faecal microbiota, (2) feed fermentation in vitro, or, (3) host metabolome.

Results

Moxidectin increased the relative abundance of Deferribacter spp. and Spirochaetes spp. observed after 160 h in moxidectin treated horses. Reduced in vitro fibre fermentation was observed 16 h following moxidectin administration in vivo (P = 0.001), along with lower pH in the in vitro fermentations from the moxidectin treated group. Metabolic profiles from urine samples did not differ between the treatment groups. However metabolic profiles from in vitro fermentations differed between moxidectin and control groups 16 h after treatment (R² = 0.69, Q²Y = 0.48), and within the moxidectin group between 16 h and 160 h post moxidectin treatment (R² = 0.79, Q²Y = 0.77). Metabolic profiles from in vitro fermentations and fermentation kinetics both indicated altered carbohydrate metabolism following in vivo treatment with moxidectin.

Conclusions

These data suggest that in horses with low parasite burdens moxidectin had a small but measurable effect on both the community structure and the function of the gut microbiome.

The grain boundary effect on mechanical and electronic transport properties of a striped borophene

The grain boundary (GB) effect on the mechanical and electronic transport properties of a striped borophene are investigated based on first principles calculations. Three GBs, (1,2)|(1,2), (2,1)|(2,1) and (3,1)|(3,1), constructed using the translation vector method are verified to possess low formation energy and stability at room temperature. The presence of GBs does not destroy the metallic nature of borophene, but results in the accumulation of charge densities. The mechanical strength of borophene is decreased due to the introduction of GBs. Their fracture behaviors are more complex, accompanied by reconstructions in the GB region. The transport current is also degraded, which is mainly caused by GBs in the borophene giving rise to backscattering. The degree of these reductions rely on the specific structure of GBs.

Effects of EGCG on proliferation and apoptosis of gastric cancer SGC7901 cells via down-regulation of HIF-1α and VEGF under a hypoxic state

OBJECTIVE

To investigate the effects of epigallocatechin-3-gallate (EGCG) on proliferation and apoptosis of human gastric cancer SGC7901 cells under a hypoxic state.

MATERIALS AND METHODS

Human gastric cancer SGC7901 cells were sub-cultured, and the cobalt chloride (CoCl2) hypoxia model was established. The blank control group (normoxia group), hypoxia control group (hypoxia group) and hypoxia + different concentrations of EGCG subgroups (20, 40, 60, 80, 100 μg/mL EGCG) were set up. Cell viability was detected via methyl thiazolyl tetrazolium (MTT) assay, apoptosis was detected via flow cytometry, and expressions of hypoxia-inducible factor-1α (HIF-1α) and vascular endothelial growth factor (VEGF) were detected via reverse transcription-polymerase chain reaction (RT-PCR) and Western blotting.

RESULTS

Relatively low concentrations of EGCG (20-80 μg/mL) presented no significant inhibiting effect on SGC7901 cell growth within a short time (24 h) (p>0.05). The increasing concentration of EGCG inhibited cell proliferation under a hypoxia state (p<0.05). EGCG induced apoptosis in a dose-dependent manner under hypoxia (p<0.05). EGCG could significantly impede expressions of HIF-1α and VEGF proteins (p<0.05), and down-regulate the level of VEGF mRNA (p<0.05), but it showed no significant effect on the HIF-1α mRNA expression (p>0.05).

CONCLUSIONS

EGCG inhibited cell proliferation under hypoxia via the downregulation of HIF-1α and its downstream target gene VEGF levels, providing a theoretical basis for the early diagnosis and treatment of gastric cancer in clinic.

Two-dimensional stable Mn based half metal and antiferromagnets promising for spintronics

In this paper, we predict that the tetragonal MnSi and MnC0.5Si0.5 monolayers are mechanically stable metallic ferromagnetic materials. The thermal stability of the MnC0.5Si0.5 monolayer is verified by our ab initio molecular dynamics (AIMD) result at 300 K. Both MnSi and MnC0.5Si0.5 monolayers exhibit room temperature half-metallic properties, which is very promising for spintronic applications. Both monolayers exhibit large perpendicular magnetic anisotropy, which is desirable for maintaining magnetic order and for high density storage spintronics. A bilayer of the MnSi nanosheet has obviously enhanced thermal stability and exhibits antiferromagnetic metal properties. The Néel temperature could be effectively manipulated and improved by surface functionalization. In addition, monolayer and bilayer MnSi nanosheets exhibit nodal lines in the reciprocal space, and the nodal lines are robust against spin orbit coupling.

Higher thyroid-stimulating hormone levels in the first trimester are associated with gestational diabetes in a Chinese population

AIM

To evaluate the relationship between maternal thyroid-stimulating hormone levels during the first trimester and gestational diabetes risk.

METHODS

In Tianjin, China, 7258 women underwent a thyroid-stimulating hormone screening test within 12 gestational weeks and then had a glucose challenge test at 24-28 weeks of gestational age. The women with a glucose challenge test ≥7.8 mmol/l underwent a 75 g oral glucose tolerance test. Gestational diabetes was diagnosed following International Association of Diabetes and Pregnancy Study Group criteria. Restricted cubic spline analysis was performed to explore full-range risk associations of thyroid-stimulating hormone levels with gestational diabetes. Logistic regression was performed to obtain odds ratios and 95% confidence intervals.

RESULTS

In all, 594 women (8.2%) had gestational diabetes. Among women with thyroid-stimulating hormone ≤3.2 mIU/l, a positive association between thyroid-stimulating hormone levels and gestational diabetes risk was found (adjusted OR: 1.13, 95% CI: 1.00-1.27). There was no relationship between thyroid-stimulating hormone levels and gestational diabetes risk in univariable and multivariable analyses among women with thyroid-stimulating hormone >3.2 mIU/l. In subgroup analyses, among women with thyroid-stimulating hormone ≤3.2 mIU/l and BMI ≥25 kg/m² , the adjusted odds ratio for thyroid-stimulating hormone levels with gestational diabetes was enhanced to 1.25 (95% CI: 1.02-1.53).

CONCLUSIONS

In pregnant Chinese women, thyroid-stimulating hormone levels even within normal range in the first trimester were positively related to gestational diabetes risk, especially for pre-pregnancy overweight/obese women.

Community health perceptions and human environmental exposure to chromium contamination in a small New Jersey City

Following a 1983 chromic acid (hexavalent chromium [CrVI]) spill from a Garfield, NJ electroplating plant, CrVI-contaminated water was found in a local firehouse basement in 1993. An ATSDR public health advisory was issued for the plant site in 2010, and from 2008-2015, fourteen residential properties have required remediation to address CrVI-contaminated dust in the basements. As part of the Community Outreach and Engagement Core of the NYU NIEHS Center, seventytwo Garfield residents aged 18-65 years, participated in a community survey with the goal of identifying concerns related to environmental and community health. Thirty-two percent responded that they 'didn't know' if they were exposed to chemicals or pollutants where they live. This finding suggests a limited awareness of environmental chemical exposures, chromium contamination and/or potential exposure to CrVI. Furthermore, toenail clippings were collected from forty-seven Garfield residents and analyzed for total chromium levels to assess potential long-term exposure. On average, residents living on/inside the contaminated plume area had higher total chromium levels in their toenail clippings than residents living outside the plume area. However, chromium levels for all participants were within the range of historical normal. This study highlights the value of partnerships between environmentally-impacted community's and academic scientists working together to identify potential contaminant exposures and address public health concerns through research and environmental health education.

High-Temperature Continuous-Wave Pumped Lasing from Large-Area Monolayer Semiconductors Grown by Chemical Vapor Deposition

The realization of low-energy-consumption lasers based on atomically thin two-dimensional (2D) transition metal dichalcogenides (TMDCs) is crucial for the development of optical communications, flexible displays, and lasers on the chip level. However, among the as-demonstrated TMDC-based lasers so far, the gain materials are mainly achieved by a mechanical exfoliation approach accompanied by poor reproducibility and controllability. In this work, we report a controllable design for generating large-scale lasing from chemical vapor deposition (CVD)-derived high-quality monolayer MoS₂ film. Strong continuous-wave optically driven whispering-gallery-mode lasing is achieved in a wide temperature range from 77 to 400 K. The eminent lasing performances result from the strong spatial confinement of carriers and the enhanced efficiency of spontaneous emission owing to the lensing and screening effects of silica microsphere cavities. These findings not only advance the fundamental understanding of 2D lasing effects but also provide solutions to fabricate low-cost, scalable, and integratable TMDC-based lasers.

Development and Validation of a Natural Language Processing Tool to Identify Patients Treated for Pneumonia across VA Emergency Departments

BACKGROUND

Identifying pneumonia using diagnosis codes alone may be insufficient for research on clinical decision making. Natural language processing (NLP) may enable the inclusion of cases missed by diagnosis codes.

OBJECTIVES

This article (1) develops a NLP tool that identifies the clinical assertion of pneumonia from physician emergency department (ED) notes, and (2) compares classification methods using diagnosis codes versus NLP against a gold standard of manual chart review to identify patients initially treated for pneumonia.

METHODS

Among a national population of ED visits occurring between 2006 and 2012 across the Veterans Affairs health system, we extracted 811 physician documents containing search terms for pneumonia for training, and 100 random documents for validation. Two reviewers annotated span- and document-level classifications of the clinical assertion of pneumonia. An NLP tool using a support vector machine was trained on the enriched documents. We extracted diagnosis codes assigned in the ED and upon hospital discharge and calculated performance characteristics for diagnosis codes, NLP, and NLP plus diagnosis codes against manual review in training and validation sets.

RESULTS

Among the training documents, 51% contained clinical assertions of pneumonia; in the validation set, 9% were classified with pneumonia, of which 100% contained pneumonia search terms. After enriching with search terms, the NLP system alone demonstrated a recall/sensitivity of 0.72 (training) and 0.55 (validation), and a precision/positive predictive value (PPV) of 0.89 (training) and 0.71 (validation). ED-assigned diagnostic codes demonstrated lower recall/sensitivity (0.48 and 0.44) but higher precision/PPV (0.95 in training, 1.0 in validation); the NLP system identified more "possible-treated" cases than diagnostic coding. An approach combining NLP and ED-assigned diagnostic coding classification achieved the best performance (sensitivity 0.89 and PPV 0.80).

CONCLUSION

System-wide application of NLP to clinical text can increase capture of initial diagnostic hypotheses, an important inclusion when studying diagnosis and clinical decision-making under uncertainty.

DFT modelling of a diphosphane - N-heterocyclic carbene-Rh(i) pincer complex rearrangement: a computational evaluation of the electronic effects in C-P bond activation

DFT calculations confirmed that the rearrangement of a PCP-Rh-H pincer to a CCP-Rh-phosphane pincer occured by C-P oxidative addition (ΔG^‡ = 29.5 kcal mol^-1, rate-determining step), followed by P-H reductive elimination (ΔG^‡ = 4.8 kcal mol^-1). The oxidative addition proceeded via a 3-centered transition state and is accelerated by electron-withdrawing substituents p- to the reacting C-P bond, resulting in a reaction constant (ρ) of 2.12 for ΔG^‡ and 2.76 for ΔH^‡ in a Hammett-type linear free energy relationship. AIM wavefunction analyses indicated a decrease in the negative charge on the carbon bonded to Rh with a concomitant increase in the positive charge on the latter. The electronic density at the Rh-P bond critical point and the atomic charge on Rh correlate well with the Hammett constants (σ) of the p-substituents. The replacement of the Rh-bound hydride with other anions (CH₃, Ph, t-Bu, OH, F, Cl, and CN) results in a decrease in the OA barrier only for CH₃, which is in accordance with the experimental results. The reductive elimination occurs via a 3-centered (Rh, H, P) transition state, which adopts a conformation wherein the steric clash between the i-Pr groups is minimized, followed by recomplexation of Rh and the newly formed (i-Pr)₂PH by a conformational twist around the Rh-P axis.

Hypertensive disorders of pregnancy in women with gestational diabetes mellitus on overweight status of their children

Hypertensive disorders of pregnancy (HDP) as a group of medical complications in pregnancy are believed to be associated with an increased risk of poor fetal growth, but the influence on offspring’s body composition is not clear. The aim of the present study was to evaluate the association between maternal hypertensive disorders of pregnancy and overweight status in the offspring of mothers with gestational diabetes mellitus (GDM).

A cross-sectional study among 1263 GDM mother-child pairs was performed in Tianjin, China. General linear models and logistic regression models were used to assess the associations of maternal hypertension in pregnancy with anthropometry and overweight status in the offspring from birth to 1–5 years old.

Offspring of GDM mothers who were diagnosed with hypertensive disorders during pregnancy had higher mean values of Z scores for birth weight for gestational age and birth weight for length, and higher mean values of Z scores for weight for age, weight for length/height, and body mass index for age at 1–5 years old than those of GDM mothers with normal blood pressure during pregnancy. Maternal hypertensive disorders of pregnancy were associated with increased risks of large for gestational age (OR 1.74, 95%CI 1.08–2.79) and macrosomia (OR 2.02, 95%CI 1.23–3.31) at birth and childhood overweight/obesity at 1–5 years old age (OR 1.88, 95%CI 1.16–3.04).

For offspring of mothers with GDM, maternal hypertension during pregnancy was a risk factor for macrosomia at birth and childhood overweight and obesity, and controlling the maternal hypertension may be more important for preventing large for gestational age babies and childhood obesity.